Vulnerability Details : CVE-2021-29546

Potential exploit
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Published 2021-05-14 20:15:13
Updated 2021-07-26 16:05:50
Source GitHub, Inc.
View at NVD,   CVE.org

Products affected by CVE-2021-29546

Exploit prediction scoring system (EPSS) score for CVE-2021-29546

EPSS FAQ
0.04%
Probability of exploitation activity in the next 30 days EPSS Score History
~ 5 %
Percentile, the proportion of vulnerabilities that are scored at or less

CVSS scores for CVE-2021-29546

Base Score Base Severity CVSS Vector Exploitability Score Impact Score Score Source First Seen
4.6
 MEDIUM AV:L/AC:L/Au:N/C:P/I:P/A:P
3.9
6.4
 NIST
7.8
 HIGH CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
1.8
5.9
 NIST
2.5
 LOW CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
1.0
1.4
 GitHub, Inc.

CWE ids for CVE-2021-29546

  • The product divides a value by zero.
    Assigned by: security-advisories@github.com (Primary)

References for CVE-2021-29546

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